AIMC Topic: Emergency Service, Hospital

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Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test.

The Lancet. Digital health Dec 11, 2020
BACKGROUND: The early clinical course of COVID-19 can be difficult to distinguish from other illnesses driving presentation to hospital. However, viral-specific PCR testing has limited sensitivity and results can take up to 72 h for operational reaso...
Mass Screening Predictive Value of Tests Triage Emergency Service, Hospital Hematologic Tests Hospitalization Adult Middle Aged Hospitals Artificial Intelligence COVID-19 Prospective Studies Humans
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A randomized trial of robot-based distraction to reduce children's distress and pain during intravenous insertion in the emergency department.

CJEM Dec 10, 2020
OBJECTIVES: Our objectives were to evaluate the effectiveness of humanoid robot-based distraction on reducing distress and pain in children undergoing intravenous insertion.
Male Humans Pain Child Robotics Pain Management Emergency Service, Hospital Pain, Procedural
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Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.

Journal of medical Internet research Dec 2, 2020
BACKGROUND: Conventional diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) testing (hereafter, PCR) is associated with prolonged time to diagnosis and significant costs to run the test. The SARS-CoV-2 virus might lea...
SARS-CoV-2 Aged Adult Sensitivity and Specificity COVID-19 Female Reproducibility of Results Area Under Curve Humans Emergency Service, Hospital Male Laboratories Machine Learning Middle Aged Hematologic Tests Pandemics Hospitals ROC Curve
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Development of a Machine Learning Model Using Multiple, Heterogeneous Data Sources to Estimate Weekly US Suicide Fatalities.

JAMA network open Dec 1, 2020
IMPORTANCE: Suicide is a leading cause of death in the US. However, official national statistics on suicide rates are delayed by 1 to 2 years, hampering evidence-based public health planning and decision-making.
United States Public Health Surveillance Emergency Service, Hospital Information Storage and Retrieval Cross-Sectional Studies Public Health Suicide Humans Machine Learning Forecasting
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Using machine learning tools to predict outcomes for emergency department intensive care unit patients.

Scientific reports Dec 1, 2020
The number of critically ill patients has increased globally along with the rise in emergency visits. Mortality prediction for critical patients is vital for emergency care, which affects the distribution of emergency resources. Traditional scoring s...
Aged Male Middle Aged ROC Curve Humans Machine Learning Intensive Care Units Female Models, Biological Treatment Outcome Area Under Curve Emergency Service, Hospital
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Transfer learning with chest X-rays for ER patient classification.

Scientific reports Dec 1, 2020
One of the challenges with urgent evaluation of patients with acute respiratory distress syndrome (ARDS) in the emergency room (ER) is distinguishing between cardiac vs infectious etiologies for their pulmonary findings. We conducted a retrospective ...
Respiratory Distress Syndrome Emergency Service, Hospital Humans Radiography, Thoracic Disease Patients Retrospective Studies Deep Learning
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Machine learning models predict coagulopathy in spontaneous intracerebral hemorrhage patients in ER.

CNS neuroscience & therapeutics Nov 28, 2020
AIMS: Coagulation abnormality is one of the primary concerns for patients with spontaneous intracerebral hemorrhage admitted to ER. Conventional laboratory indicators require hours for coagulopathy diagnosis, which brings difficulties for appropriate...
Middle Aged Cohort Studies Cerebral Hemorrhage Predictive Value of Tests Emergency Service, Hospital Blood Coagulation Disorders Female Aged Adult Humans Male Machine Learning Algorithms Retrospective Studies
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Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography.

Current problems in diagnostic radiology Nov 15, 2020
OBJECTIVE: The timely reporting of critical results in radiology is paramount to improved patient outcomes. Artificial intelligence has the ability to improve quality by optimizing clinical radiology workflows. We sought to determine the impact of a ...
Humans Artificial Intelligence Emergency Service, Hospital Benchmarking Intracranial Hemorrhages Machine Learning Retrospective Studies Tomography, X-Ray Computed
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Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing.

Journal of medical Internet research Oct 28, 2020
BACKGROUND: Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and artificial intelligence are widely used in the realms of health and medicine, researchers are only ...
Aged Adult Male Middle Aged Female SARS-CoV-2 Hospitalization Spain Machine Learning Betacoronavirus Treatment Outcome Pneumonia, Viral Prognosis Pandemics Humans Natural Language Processing Retrospective Studies COVID-19 Emergency Service, Hospital Intensive Care Units Coronavirus Infections Electronic Health Records
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The niche of artificial intelligence in trauma and emergency medicine.

The American journal of emergency medicine Oct 27, 2020
Emergency Service, Hospital Humans Artificial Intelligence Traumatology Triage Emergency Medicine
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